Ser Zheng, Sobota Radoslaw M
Functional Proteomics Laboratory, SingMass National Laboratory, Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.
Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.
Proteomics. 2025 Feb;25(3):e2400147. doi: 10.1002/pmic.202400147. Epub 2024 Nov 7.
Drug protein-target identification in past decades required screening compound libraries against known proteins to determine drugs binding to specific protein. Protein targets used in drug-target screening were selected predominantly used laborious genetic manipulation assays. In 2013, a team led by Pär Nordlund from Karolinska Institutet (Stockholm, Sweden) developed Cellular Thermal Shift Assay (CETSA), a method which, for the first time, enabled the possibility of drug protein-target identification in the complex cellular proteome. High throughput, quantitative mass spectrometry (MS) proteomics appeared as a compatible analytical method of choice to complement CETSA, aka Thermal Protein Profiling assay (TPP). Since the seminal CETSA-MS/ TPP-MS publications, different protein-target deconvolution strategies emerged including Proteome Integral Solubility Alteration (PISA). The work of Emery-Corbin et al. (Proteomics 2024, 2300644), titled Proteome Integral Solubility Alteration via label-free DIA approach (PISA-DIA), introduces Data-Independent Acquisition (DIA) as a quantification method, opening new avenues in drug target-deconvolution field. Application of DIA for target deconvolution offers attractive alternative to widely used data dependent methodology.
在过去几十年中，药物蛋白靶点的鉴定需要针对已知蛋白质筛选化合物库，以确定与特定蛋白质结合的药物。药物靶点筛选中使用的蛋白质靶点主要是通过费力的基因操作分析来选择的。2013年，由瑞典斯德哥尔摩卡罗林斯卡学院的帕尔·诺德伦德领导的一个团队开发了细胞热位移分析（CETSA），这是一种首次能够在复杂细胞蛋白质组中鉴定药物蛋白靶点的方法。高通量定量质谱（MS）蛋白质组学作为一种兼容的分析方法出现，以补充CETSA，即热蛋白质谱分析（TPP）。自从开创性的CETSA-MS/TPP-MS发表以来，出现了不同的蛋白质靶点反卷积策略，包括蛋白质组整体溶解度改变（PISA）。埃默里 - 科尔宾等人（《蛋白质组学》2024年，2300644）题为“通过无标记DIA方法进行蛋白质组整体溶解度改变（PISA-DIA）”的工作引入了数据非依赖采集（DIA）作为一种定量方法，为药物靶点反卷积领域开辟了新途径。将DIA应用于靶点反卷积为广泛使用的数据依赖方法提供了有吸引力的替代方案。
